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Automated driving recognition technologies for adverse weather conditions
Authors:Keisuke Yoneda  Naoki Suganuma  Ryo Yanase  Mohammad Aldibaja
Abstract:During automated driving in urban areas, decisions must be made while recognizing the surrounding environment using sensors such as camera, Light Detection and Ranging (LiDAR), millimeter-wave radar (MWR), and the global navigation satellite system (GNSS). The ability to drive under various environmental conditions is an important issue for automated driving on any road. In order to introduce the automated vehicles into the markets, the ability to evaluate various traffic conditions and navigate safely presents serious challenges. Another important challenge is the development of a robust recognition system can account for adverse weather conditions. Sun glare, rain, fog, and snow are adverse weather conditions that can occur in the driving environment. This paper summarizes research focused on automated driving technologies and discuss challenges to identifying adverse weather and other situations that make driving difficult, thus complicating the introduction of automated vehicles to the market.
Keywords:Corresponding author    Automated vehicle  Self-localization  Surrounding recognition  Path planning  Adverse condition
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